Abstract：
Colorimetric sensors play a crucial role in promoting on-site testing, enabling the detection and/or quantification of various analytes based on changes in color. These sensors offer several advantages, such as simplicity, cost-effectiveness, and visual readouts, making them suitable for a wide range of applications, including food safety and monitoring. A critical component in portable colorimetric sensors involves their integration with color models for effective analysis and interpretation of output signals. The most commonly used models include CIELAB (Commission Internationale de l\'Eclairage), RGB (Red, Green, Blue), and HSV (Hue, Saturation, Value). This review outlines the use of color models via digitalization in sensing applications within the food safety and monitoring field. Additionally, challenges, future directions, and considerations are discussed, highlighting a significant gap in integrating a comparative analysis toward determining the color model that results in the highest sensor performance. The aim of this review is to underline the potential of this integration in mitigating the global impact of food spoilage and contamination on health and the economy, proposing a multidisciplinary approach to harness the full capabilities of colorimetric sensors in ensuring food safety.
摘要：
比色传感器在促进现场测试中起着至关重要的作用，使得能够基于颜色的变化来检测和/或定量各种分析物。这些传感器提供了几个优点，比如简单，成本效益，和视觉读数，使它们适合广泛的应用，包括食品安全和监测。便携式比色传感器中的关键组件涉及它们与颜色模型的集成，以有效分析和解释输出信号。最常用的模型包括CIELAB（国际委员会），RGB(红色,绿色,蓝色),和HSV（色调，饱和度,值）。这篇综述概述了通过数字化在食品安全和监测领域的传感应用中使用颜色模型。此外,挑战,未来的方向,并讨论了一些考虑因素，突出了在集成比较分析以确定导致最高传感器性能的颜色模型方面的显着差距。本次审查的目的是强调这种整合在减轻食品腐败和污染对健康和经济的全球影响方面的潜力，提出了一种多学科方法来利用比色传感器的全部功能来确保食品安全。本文受版权保护。保留所有权利。
